Connected and automated vehicles can make roads safer, less congested, and more energy-efficient, but realizing these benefits requires vehicles to coordinate their actions at conflict points such as highway merges, weaving sections, and unsignalized intersections. Existing cooperative driving approaches based on status- or intent-sharing improve situational awareness but do not ensure system-wide performance improvement. Among emerging cooperation modes, agreement-seeking cooperation, in which one vehicle proposes a coordinated maneuver and each affected vehicle independently accepts or rejects it before acting, is the most practical for near-term deployment because it works in mixed traffic and preserves vehicle autonomy. However, the negotiation logic, decision-making strategies, and communication requirements needed to make agreement-seeking work reliably in real traffic are not yet defined. This project develops and evaluates an agreement-seeking cooperative driving framework for high-conflict scenarios, such as on-ramp merging, lane changes, weaving sections, and unsignalized intersections. The team will design negotiation and decision-making algorithms, build a simulation environment, and test performance across a range of automated-vehicle market shares and vehicle-to-vehicle communication conditions, measuring safety, traffic efficiency, and energy use. Public and private stakeholders will be engaged throughout the project to ensure that scenarios, assumptions, and findings are useful for real deployment. The project will provide foundational evidence to support emerging cooperative driving standards and inform agency deployment guidance.